Knowledge discovery and Data Mining (Knowledge Discovery in Databases-KDD) is a new research field which incorporates methodologies from artificial intelligence, data bases, and statistics to address the problem of discovering novel, interesting and useful patterns (knowledge) hidden in large databases. A prototype KDD surveillance system for epidemiology named Hawkeye has been developed at UAB. The goal of this research project is to further develop Hawkeye into a useful, general-purpose KDD surveillance system for epidemiology. This will be accomplished in two ways. First, experiments with the prototype system will be conducted using hospital infection control data and public health data (CDC). These experiments will enlist infection control experts, and epidemiologists. Objective results and subjective feedback will be obtained. These application-based experiments will further efforts in addressing fundamental research issues. Second, specific methods improving the presentation of discovered knowledge to the user will be defined and implemented. These methods make use of a novel idea called a phenomenon cluster.